Alternatives
Products that do what Achilles – Automatic profiling and C++ optimization of Python via LLMs does
Hey HN! We built Achilles, a tool that automatically accelerates your Python code. It identifies performance bottlenecks, rewrites those functions in optimized C++, and seamlessly patches them into your running program—without you changing a single line of code. In CPU-intensive, loop-heavy tasks, we've observed performance improvements of 100-1000x. Achilles can be installed via pip and works with just a single command. We'd appreciate your feedback, and feel free to give us a star if you find it interesting!
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2018 · github.com
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2014 · github.com
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2017 · github.com
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2019 · fastapi.tiangolo.com
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2021 · github.com
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2019 · xmake.io
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2017 · github.com
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Hello, I have several years of experience as a Python developer, and during that time, I've worked on intricate applications dealing with large volumes of data. One frequent challenge I faced was benchmarking the application and identifying performance bottlenecks. While there are some excellent Python profiling tools available, they can be quite daunting for beginners. The utility I have developed simplifies this process, making it as straightforward as possible to transition from slow code to a detailed flame chart. I would greatly appreciate your feedback!
2023 · github.com
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Quick note on how it works and how I've done my batch embedding engine IgniteMS. The whole thing runs as one process using Rust, reading input, tokenizing, packing batches, keeping the queue full. TensorRT handles inference. Python is only as a wrapper. I built it this way because when you use more than couple of GPUs, the GPUs stop being the problem. CPU cannot feed them fast enough. One A100 can go through batches faster than Python can tokenize and feed, so the GPU just sits there idle waiting for work. Most of my time went into optimizing this. At 8 GPUs that was basically the entire…
Jun 2026 · github.com
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We built RapidFire AI, an open-source Python tool to speed up LLM fine-tuning and post-training with a powerful level of control not found in most tools: Stop, resume, clone-modify and warm-start configs on the fly—so you can branch experiments while they’re running instead of starting from scratch or running one after another. - Works within your OSS stack: PyTorch, HuggingFace TRL/PEFT), MLflow. - Hyperparallel search: launch as many configs as you want together, even on a single GPU - Dynamic real-time control: stop laggards, resume them later to revisit, branch promising configs in…
Sep 2025 · github.com
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Recently, I saw few Python accelerators getting a lot of attention, and I thought it would be a good time to finally present the project that we will make available to test in the upcoming days. Flyable is an ahead-of-time compiler that takes your Python code, analyses it, and outputs very optimized machine code. Micro-benchmarks show that it produces programs that run between 10-70x time faster than Python. Flyable is certainly one of the fastest and easiest ways to accelerate your Python code. It finally allows Python to compete in the ring of fast and efficient languages without having to…
2020
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2018 · pablasso.com
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https://github.com/gugarosa/opytimizer Did you ever reach a bottleneck in your computational experiments? Are you tired of selecting suitable parameters for a chosen technique? If yes, Opytimizer is the real deal! This package provides an easy-to-go implementation of meta-heuristic optimizations. From agents to search space, from internal functions to external communication, we will foster all research related to optimizing stuff. Use Opytimizer if you need a library or wish to: - Create your optimization algorithm; - Design or use pre-loaded optimization tasks; -…
2021
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2015 · github.com
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Hi HN, We’ve all accepted the "Python tax"—you trade execution speed for developer happiness. But what if that trade-off was a thing of the past? I just came across BustAPI, and it’s basically a "cheat code" for Python web services. It’s not just another wrapper; it’s a hybrid engine that embeds a Rust (Actix-Web) core directly into the Python runtime. Is this the end of the "slow Python" era? The benchmarks are pretty shocking. I’d love to see someone stress-test this against a production-grade Go or Node.js setup. Repo: https://github.com/GrandpaEJ/BustAPI Benchmarks:…
Dec 2025 · github.com
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We combined Stanford's ACE (agents learning from execution feedback) with the Reflective Language Model pattern. Instead of reading traces in a single pass, an LLM writes and runs Python in a sandbox to programmatically explore them - finding cross-trace patterns that single-pass analysis misses. The framework achieved 2x consistency improvement on τ2-bench.
Mar 2026 · github.com
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2016 · github.com
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2020 · github.com
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